Abstract
Text sentiment analysis is a new branch of computational linguistics which is widely concerned. In this paper, we present an approach to determine polarity of sentiment word based on context of sentence. We first change the context of sentence to semantic pattern vector, calculate the between different sentences, then compare sentences context indirectly by comparing similarity of their pattern vector, next we annotate polarity of sentiment word according to comparing result. Experiment shows that when the context of two sentences have high similarity, it is likely to have high precision in recognizing polarity of sentiment word. Our study shows it's feasible to use semantic pattern vector in representing context and judging polarity of sentiment words.
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